Thanks so much ! But i have this type of results, not so smooth … somebody had the solution ? thanks
You seem to work in CPU mode, where the volumes are downsampled for the segmentation. Invest in a CUDA-enabled GPU to get better results. You could also smooth your segmentations in the segment editor.
Yess i’m actually work with a macbook pro m2 pro.
Apple hardware has no CUDA-enabled GPU unfortunately.
Apple has some hardware acceleration that PyTorch may be able to utilize, so it is worth trying the full-quality mode (disable “fast” option) and see what segmentation quality you can get and with what computation time.
If you don’t want to invest into buying a computer that has a CUDA-capable GPU then you can rent a GPU-equipped virtual machine from Amazon/Microsoft/Google and install&run Slicer there.
If you are a researcher funded by the US government, it is rather easy to get access to a VM desktop with GPU via ACCESS allocation - quite a few of us in the IDC team have been using those VMs exactly for the purpose of testing/using Slicer functionality that requires GPU: ACCESS allocations - IDC User Guide.
Thanks for your updating. It looks amazing on adult! But do you think it will also work well for infants?
Also do those training data cover infant whole body CT images, since I am interested in infant whole body segmentation!
The model had been trained on a very wide variety of data. It can even pick up some anatomy on animal CTs (for example on swine images, ribs and spine was segmented well, liver was found but segmented inaccurately). I would expect that it would work fairly well on human infant CTs, but please try and let us know.